TY - JOUR
T1 - A MoliZoft System Identification Approach of the Just Walk Data
AU - dos Santos, P. Lopes
AU - Freigoun, M. T.
AU - Rivera, Daniel
AU - Hekler, E. B.
AU - Martín, C. A.
AU - Romano, R.
AU - Perdicoúlis, T. P.
AU - Ramos, J. A.
N1 - Funding Information:
P.Lopes dos was supported by FCT through grant SFRH/BSAB/11383572015 and by the Research Center Research Center for Systems and Technology (SYSTEC) of Faculdade de Engenharia da Universidade do Porto. Support for the ASU authors has been provided by the National Science Foundation (NSF) through grant IIS-1449751. The opinions expressed in this article are the authors’ own and do not necessarily reflect the views of NSF.
Publisher Copyright:
© 2017
PY - 2017/7
Y1 - 2017/7
N2 - A system identification approach is used estimate linear time invariant models from the data of physical activity gathered in the Just Walk intervention conducted by the Designing Health Lab and the Control Systems Laboratory at Arizona State University A class of identification algorithms proposed elsewhere by one of the authors, denoted as MoliZoft, was reformulated and adapted to estimate models from data gathered in this experience. In this paper, the identification algorithms are described and the best models estimated for a particular participant are analysed and used to improve the results in future experiments.
AB - A system identification approach is used estimate linear time invariant models from the data of physical activity gathered in the Just Walk intervention conducted by the Designing Health Lab and the Control Systems Laboratory at Arizona State University A class of identification algorithms proposed elsewhere by one of the authors, denoted as MoliZoft, was reformulated and adapted to estimate models from data gathered in this experience. In this paper, the identification algorithms are described and the best models estimated for a particular participant are analysed and used to improve the results in future experiments.
KW - Least squares identification
KW - Output error identification
KW - Prediction error methods
KW - Social
KW - System identification
KW - behavioural sciences
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U2 - 10.1016/j.ifacol.2017.08.2060
DO - 10.1016/j.ifacol.2017.08.2060
M3 - Article
AN - SCOPUS:85044864674
SN - 2405-8963
VL - 50
SP - 12508
EP - 12513
JO - 20th IFAC World Congress
JF - 20th IFAC World Congress
IS - 1
ER -